Adhesion molecule gene variants and plasma protein levels in patients with suspected obstructive sleep apnea
Bibliographic record
Abstract
STUDY OBJECTIVES: Untreated obstructive sleep apnea (OSA) patients have an increased risk of cardiovascular disease (CVD). Adhesion molecules, including soluble E-selectin (sE-selectin), intercellular adhesion molecule-1 (ICAM-1), and vascular adhesion molecule-1 (VCAM-1), are associated with incident CVD. We hypothesized that specific genetic variants will be associated with plasma levels of adhesion molecules in suspected OSA patients. We also hypothesized that there may be an interaction between these variants and OSA. METHODS: We measured levels of sE-selectin, sICAM-1 and sVCAM-1 in 491 patients with suspected OSA and genotyped them for 20 polymorphisms. RESULTS: The most significant association was between the ABO rs579459 polymorphism and sE-selectin levels (P = 7×10-21), with the major allele T associated with higher levels. The direction of effect and proportion of the variance in sE-selectin levels accounted for by rs579459 (16%) was consistent with estimates from non-OSA cohorts. In a multivariate regression analysis, addition of rs579459 improved the model performance in predicting sE-selectin levels. Three polymorphisms were nominally associated with sICAM-1 levels but none with sVCAM-1 levels. The combination of severe OSA and two rs579459 T alleles identified a group of patients with high sE-selectin levels; however, the increase in sE-selectin levels associated with severe OSA was greater in patients without two T alleles (P = 0.05 test for interaction). CONCLUSIONS: These genetic polymorphisms may help to identify patients at greatest risk of incident CVD and may help in developing a more precision-based approach to OSA care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".